activity
20192023
most citedStageNet: Stage-Aware Neural Networks for Health Risk Prediction

79 citations · 123 across the 12 of their papers we have counts for

collaborators

12 papers

cs.LG2023★ 3 cited

MFair: Mitigating Bias in Healthcare Data through Multi-Level and Multi-Sensitive-Attribute Reweighting Method

Yinghao Zhu, Jingkun An, Enshen Zhou +8

In the data-driven artificial intelligence paradigm, models heavily rely on large amounts of training data. However, factors like sampling distribution imbalance can lead to issues…

cs.LG2023★ 1 cited

Mortality Prediction with Adaptive Feature Importance Recalibration for Peritoneal Dialysis Patients: a deep-learning-based study on a real-world longitudinal follow-up dataset

Liantao Ma, Chaohe Zhang, Junyi Gao +8

Objective: Peritoneal Dialysis (PD) is one of the most widely used life-supporting therapies for patients with End-Stage Renal Disease (ESRD). Predicting mortality risk and identif…

cs.LG2022

A Comprehensive Benchmark for COVID-19 Predictive Modeling Using Electronic Health Records in Intensive Care

Junyi Gao, Yinghao Zhu, Wenqing Wang +4

The COVID-19 pandemic has posed a heavy burden to the healthcare system worldwide and caused huge social disruption and economic loss. Many deep learning models have been proposed…

cs.LG2022★ 2 cited

MedML: Fusing Medical Knowledge and Machine Learning Models for Early Pediatric COVID-19 Hospitalization and Severity Prediction

Junyi Gao, Chaoqi Yang, George Heintz +7

The COVID-19 pandemic has caused devastating economic and social disruption, straining the resources of healthcare institutions worldwide. This has led to a nationwide call for mod…

cs.SI2022★ 7 cited

PopNet: Real-Time Population-Level Disease Prediction with Data Latency

Junyi Gao, Cao Xiao, Lucas M. Glass +1

Population-level disease prediction estimates the number of potential patients of particular diseases in some location at a future time based on (frequently updated) historical dis…

cs.SI2020★ 7 cited

STAN: Spatio-Temporal Attention Network for Pandemic Prediction Using Real World Evidence

Junyi Gao, Rakshith Sharma, Cheng Qian +5

Objective: The COVID-19 pandemic has created many challenges that need immediate attention. Various epidemiological and deep learning models have been developed to predict the COVI…